camir-aes2014: toolboxes/FullBNT-1.0.7/bnt/general/score_bnet

first hg version after svn

rev	line source
wolffd@0	1 function L = log_lik_complete(bnet, cases, clamped)
wolffd@0	2 % LOG_LIK_COMPLETE Compute sum_m sum_i log P(x(i,m)\| x(pi_i,m), theta_i) for a completely observed data set
wolffd@0	3 % L = log_lik_complete(bnet, cases, clamped)
wolffd@0	4 %
wolffd@0	5 % If there is a missing data, you must use an inference engine.
wolffd@0	6 % cases(i,m) is the value assigned to node i in case m.
wolffd@0	7 % (If there are vector-valued nodes, cases should be a cell array.)
wolffd@0	8 % clamped(i,m) = 1 if node i was set by intervention in case m (default: clamped = zeros)
wolffd@0	9 % Clamped nodes contribute a factor of 1.0 to the likelihood.
wolffd@0	10
wolffd@0	11 if iscell(cases), usecell = 1; else usecell = 0; end
wolffd@0	12
wolffd@0	13 n = length(bnet.dag);
wolffd@0	14 ncases = size(cases, 2);
wolffd@0	15 if n ~= size(cases, 1)
wolffd@0	16 error('data should be of size nnodes * ncases');
wolffd@0	17 end
wolffd@0	18
wolffd@0	19 if nargin < 3, clamped = zeros(n,ncases); end
wolffd@0	20
wolffd@0	21 L = 0;
wolffd@0	22 for i=1:n
wolffd@0	23 ps = parents(bnet.dag, i);
wolffd@0	24 e = bnet.equiv_class(i);
wolffd@0	25 u = find(clamped(i,:)==0);
wolffd@0	26 L = L + log_prob_node(bnet.CPD{e}, cases(i,u), cases(ps,u));
wolffd@0	27 end
wolffd@0	28

Mercurial > hg > camir-aes2014